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https://issues.apache.org/jira/browse/SPARK-32025?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17142403#comment-17142403
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Apache Spark commented on SPARK-32025:
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User 'planga82' has created a pull request for this issue:
https://github.com/apache/spark/pull/28896
> CSV schema inference with boolean & integer
> --------------------------------------------
>
> Key: SPARK-32025
> URL: https://issues.apache.org/jira/browse/SPARK-32025
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.4.6
> Reporter: Brian Wallace
> Priority: Major
>
> I have a dataset consisting of two small files in CSV format.
> {code:bash}
> $ cat /example/f0.csv
> col1
> 8589934592
> $ cat /example/f1.csv
> col1
> 43200000
> true
> {code}
>
> When I try and load this in (py)spark and infer schema, my expectation is
> that the column is inferred to be a string. However, it is inferred as a
> boolean:
> {code:python}
> spark.read.csv(path="file:///example/*.csv", header=True, inferSchema=True,
> multiLine=True).show()
> +----+
> |col1|
> +----+
> |null|
> |true|
> |null|
> +----+
> {code}
> Note that this seems to work correctly if multiLine is set to False (although
> we need to set it to True as this column may indeed span multiple lines in
> general).
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